tbuckley/cabot-search huggingface dataset:
Overcoming barriers and improving genetic testing completion rate for hereditary cancer in an underserved population at a large safety net hospital.
Authors: Autumn Vara, Tejal Amar Patel
Journal: Journal of Clinical Oncology (2023)

1538 Background: Genetic testing is a routine practice in oncology care as outcomes of germline testing may impact surgical recommendations, open therapeutic options, as well as inform patients and family members of their cancer risks. Lyndon B. Johnson Hospital (LBJ) is a safety-net hospital that mainly serves low income and uninsured patients (pts), and LBJ oncology clinic is staffed by MD Anderson Medical Oncology faculty and fellows. Pre-test counseling with a certified genetic counselor was offered once a week by referral and transitioned to virtual template at the start of the COVID-19 pandemic. This transition in addition to barriers unique to the underserved population led to a decrease in test completion rates and introduced a backlog as patients were re-referred for completion of testing. We discuss our strategies in decreasing a 9-month backlog over the course of one year. Methods: Re-introduction of an on-site general oncology genetic counselor twice a week was implemented in addition to maintaining the virtual platform once a week. The on-site genetic counselor was embedded in the physician’s clinic and rotated to ensure coverage for all clinic days. Manual chart review was conducted by on-site genetic counselor and patients were rescheduled to in-person template in conjunction with other same day appointments to improve no-show rate. Patients electing to proceed with germline testing signed appropriate written consent, patient assistance financial forms, and submitted samples prior to leaving clinic. Results: From January 2019 through December 2022, a total of 1716 patients including re-referrals were scheduled and 728 patients seen. When genetic counseling service was available as referral outside of oncology clinic, the completed visit rate was 48%, which decreased to 26% in 2020 after COVID- 19 transition to virtual. The visit completion rate did improve to 36% in 2021 but the most improvement was seen with genetic counselor embedded in physician clinic with 69% in 2022. The number of genetic testing also increased with 79 ordered in 2021 to 211 ordered in 2022. Of those patients who met national criteria for germline testing and expressed verbal consent, 47% completed germline testing in 2021 which improved to 83% in 2022. Conclusions: In our experience, telehealth genetic services is not ideal in the underserved population as there are unique barriers. On-site embedded genetic counseling helps eliminate barriers by allowing patients to complete all steps necessary prior to leaving clinic, leading to successful test completion rates and improved quality of care.[Table: see text]
Phase I and pharmacodynamic study of arsenic trioxide plus radiotherapy for newly diagnosed glioblastoma.
Authors: Samuel Ryu, Xiaobu Ye, Jeffrey J. Olson, Tom Mikkelsen, Lev Bangiyev, Glenn Jay Lesser, Tracy Batchelor, Louis B. Nabors, Serena Desideri, Tobias Walbert, Stuart A. Grossman
Journal: Journal of Clinical Oncology (2023)

2061 Background: Arsenic Trioxide (ATO) demonstrated prolonged survival in a transplanted rodent glioblastoma (GBM) model. Given the lack of effective therapies before temozolomide was available, the NCI funded NABTT Brain Tumor Consortium initiated a Phase I study of ATO with radiation in patients with newly diagnosed glioblastoma. Dose escalations using two different schedules of ATO were studied. Methods: Patients with newly diagnosed GBM (MGMT and IDH mutation status unknown) were assigned to receive ATO once or twice weekly during the 6-week course of radiation. The starting ATO dose was 0.25 mg/kg. This was escalated by 0.05 mg/kg until an MTD was reached. Patients did not receive ATO or other adjuvant therapy once the radiation was completed. As ATO affected tumor vasculature and blood flow in experimental imaging studies, perfusion MRIs were obtained before ATO administration and one and six weeks later. Survival was a secondary endpoint. Results: Thirty-one patients were enrolled: median age 54.9 years, 68% male, 77% patients KPS &gt;90, 77% had tumor resection. The MTD was determined to be 0.4mg/kg on the weekly schedule and 0.3mg/kg on the biweekly schedule. ATO was well tolerated with 81% of patients completing the 6 weeks combined treatment. Major dose limiting toxicities were increased aspartate and alanine aminotransferases and one case of hyperkalemia. For all patients the median overall survival (mOS) was 17.7 months and the median progression-free survival (mPFS) was 5.4 months. However, there was a significant survival difference between the two ATO dose schedules across all doses with a mOS of 22.8 months in the biweekly schedule, vs 12.1 months in the weekly schedule (P = 0.039). There was a similar difference in mPFS (10.2 months vs 3.2 months, respectively, P = 0.004). Similarly, there were significant differences in perfusion imaging between the two ATO dose schedules with relative cerebral blood flow showing a significant decrease after one week of ATO treatment on the biweekly schedule (p = 0.007). Conclusions: TheMTDs of ATO in patients with GBM administered once or twice weekly for six weeks with standard radiation were determined. This regimen was well tolerated. Survival in patients on the biweekly schedule was much better (22.8 months) than expected in patients not receiving temozolomide. In addition, patients on biweekly ATO also had significant changes on MRI perfusion studies suggesting a pharmacodynamic effect of this agent. These finding should be explored further in patients with newly diagnosed MGMT unmethylated GBM where temozolomide has very limited activity. Clinical trial information: NCT00045565 .
A low-cost breast cancer prognosis tool for developing countries using AI.
Authors: Iván Romarico González Espinoza, Abraham Castro-Ponce, Sergio Jiménez-Monferrer, María Castelló-Pons, Edgar E. Cardona-Ferrer, Gabriela Juárez-Salazar, Diego A. Juárez-Salazar, Ricardo I. Montes-de-Oca-Moreda, Marisela Coyotl-Huexotl, Mariana Chiquillo-Domínguez, Eric Acosta Ponce de León, José Manuel Aguilar Priego, Carlos Cordero Vargas, Carlos Alberto Cortes Garcia, Francisco J. Ceja-Utrera, Juan C. Lara-Bejarano, María de Jesús Gonzalez Blanco, Julio Cesar Garibay Diaz, Jorge E. Aranda Claussen
Journal: Journal of Clinical Oncology (2023)

e13536 Background: The use of artificial intelligence in breast cancer diagnosis has had a significant impact. Alternative to other tests, machine learning (ML) models are low-cost tools that can establish an objective prognosis by considering all the clinical, genomic, and histological data from patients. To evaluate the performance of 12 ML models in predicting the overall survival of breast cancer patients at 60 months of follow-up. Methods: Clinical data was obtained from “The Cancer Genome Atlas-Breast Cancer" database. Preprocessing of data ruled out variables with insufficient values or poor relevance. Data was divided into an 80/20 ratio to perform the training and testing of the models. The models used were: Logistic Regression (LR), Ridge Classifier (RC), Least Absolute Shrinkage and Selection Operator (LASSO), K-nearest Neighbors (KNN), Naive Bayes (NB), Linear Discriminant Analysis (LDA), Decision Tree (DT), Multilayer Perceptron (MP), Stochastic Gradient Descent (SGD), Support Vector Machine (SVM), Random Forest (RF), and XGBoost (XGB). Initial training used the default hyperparameters of each model, performance was evaluated through a 5-fold-cross-validation, the results were used with the GridSearchCV tool to optimize the hyperparameters for the final training and testing of the models. Results: The models with most accuracy were NB (86.76%) and SGD (85.29%), with most sensitivity were: SGD (93.75%), MP (91.67%) and NB (89.89%), with the most specificity were: KNN (95.0%), DT (90.0%) and LASSO (85.0%), with the highest area under the ROC curve were: LDA (90.83%), LASSO (90.1%), and LR (89.79%). The variables with the highest relevance were: "Previous diagnosis of cancer", "Presence of tumor", "Ancillary Therapy", and "Histology". Integrating the best-performing models into an interactive tool preserves the best features without sacrificing efficiency. Conclusions: The models with the best overall performance in predicting the prognosis of patients with breast cancer were NB and LASSO. The best way to evaluate the performance of a predictive prognosis tool is the area under the ROC curve. For developing countries, an AI tool to predict the patient outcome is viable when other expensive prognosis genomic tools are not available. Further studies with data from developing countries are needed to improve the performance of this tool.
Effect of national multidisciplinary tumor boards on diagnostic stratification and therapeutic management in cancers of unknown primary.
Authors: Nicolas Jacquin, Maud Kamal, Ivan Bieche, Célia Dupain, Isabelle Guillou, Etienne Rouleau, Julien Masliah-Planchon, Camille Tlemsani, Helene Blons, Laetitia Marisa, Pierre Blanc, Jennifer Wong, Pierre Saintigny, Sandrine Boyault, Yves Allory, Anne Vincent-Salomon, Vincent Cockenpot, Janick Selves, Christophe Le Tourneau, Sarah Watson
Journal: Journal of Clinical Oncology (2023)

e13666 Background: With the increasing complexity of current diagnostic investigations, the integration of clinical, pathological and genomic characteristics is crucial for the management of patients (pts) with cancers of unknown primary (CUP). A national multidisciplinary tumor board (NatCUPMTB) was created in July 2020 in France to discuss the diagnostic and therapeutic management of CUP pts. The objective of this study was to evaluate the diagnostic, prognostic and therapeutic impact of NatCUPMTB after 30 months of activity. Methods: This was a multicenter retrospective study with prospective follow-up. All pts discussed at least once in the NatCUPMTB between July 2020 and January 2023 were included. Pts and tumors characteristics, pathological and genomic analyses including WGS, WES and RNAseq performed on the two PFGM2025 (French Genomic Medecine Plan 2025) national large-scale sequencing platforms, NatCUPMTB conclusions, and follow-up were collected. Results: 151 pts were included. The median age at diagnosis was 58 yo, 55% were female, and the median number of metastatic sites at diagnosis was 2. The median time between diagnosis and first MTB presentation was 4 months (1-20). At the time of analysis, NatCUPMTB conclusions and long-term follow up were available for 92 pts. MTB investigations enabled to identify a likely primary origin in 53/92 (58%) pts, the most frequent being renal carcinoma (N=9) cholangiocarcinoma (N=6) and lung carcinoma (N=6). For 16/53 (30%) pts, MTB diagnoses were based on the combination of clinical, pathological and genomic investigations. NatCUPMTB recommended a personalized therapeutic strategy in 54/92 patients (59%). After a median follow-up of 11.2 months, the median overall survival (OS) was 17.4 months from diagnosis and 10.1 months from the 1 st MTB presentation. Pts for which the MTB had a diagnostic impact had increased OS from 1 st MTB presentation compared to pts with no diagnostic orientation (14.5 vs 4.4 months, p=0.0007). Moreover, pts having received a treatment following MTB recommendation (based on likely origin or targetable alteration) had increased OS from 1 st MTB presentation compared to pts having received other treatments (14.5 vs 4.4 months, p=0.003). Conclusions: NatCUPMTB provides significant diagnostic and therapeutic benefit in pts with CUP. Early presentation of pts at NatCUPMTB as soon as CUP diagnosis is suspected should be recommended.
Is there a harmonised standard to oncology trial data provision in data sharing initiatives?
Authors: Ashley Mark Hopkins, Natansh Modi, Michael J. Sorich
Journal: Journal of Clinical Oncology (2023)

e13645 Background: Over the past decade the pharmaceutical industry has invested considerably in data sharing infrastructures to support independent researcher access to clinical trial individual-participant data (IPD), facilitating novel secondary analyses and the development of predictive models/simulation tools. Data sharing also helps in informing trial design and can accelerate the development of new therapies. To facilitate a data sharing ecosystem achieving these visions, researchers need to be able to access data, and when they do so, optimally, the data needs to be provided in a harmonised format that supports the research. Methods: In 2021 an audit confirmed 91 (of 203) clinical trials supporting medicines approved by the FDA in the last 10 years for the treatment of solid tumours as eligible (‘in scope’) for independent IPD request. This study reports on data provision for a planned clinical trial IPD meta-analysis summarising adverse events and therapeutic outcomes for new anticancer medicines according to race and sex. For the trials shared upon request, we report the heterogeneity in provisions of IPD and supporting documents. Results: Following SAP submission, the team obtained IPD packages from 76% (69 of 91) of requested trials – this includes data from 13 companies in a pooled cohort of over 40000 patients treated with new medicines against solid tumours. Time to data provision ranged from 117 to 312 days. In the IPD packages of 7 trials, overall survival or progression-free survival data were redacted, while for 9 trials there were partial redactions to adverse event data. For 3 trials, race data was removed, and for 1, sex was removed. Age was provided as a categorised variable in 17 trials. Weight was removed from 10 trials, and performance status was removed from 2. For 19 trials no clinical study report was provided, for 4 trials the data dictionary was missing, for 18 trials there were no data derivation specifications, while 5 IPD packages did not contain files orientating to anonymisation. Conclusions: While there is room to improve and standardize data sharing principles and procedures, overall, the acquired IPD was observed as a significant and high-quality resource for future scientific discovery. Future research could consider evaluating the ability to access data from non-industry trial sponsors, and strategies to harmonise data sharing practices between companies.
A quality improvement initiative on the utility of the Oncotype DX breast cancer assay in a community hospital.
Authors: Sabah Iqbal, Krishna Desai, Bohdan Baralo, Akhil Jain, Kristal Pereira, Mahvish Renzu, Vidhi Mehta, Vartika Singh, Nithya Ramesh, Sohiel Deshpande, Vinay Edlukudige Keshava, Rajesh Thirumaran
Journal: Journal of Clinical Oncology (2023)

e13072 Background: Since the advent of Oncotype DX (ODX) breast recurrence score (RS) assay, the use of adjuvant chemotherapy (CT) in the treatment of breast cancer has significantly reduced. This test not only estimates the benefit of CT, but also determines the risk of distant recurrence in patients with early-stage breast cancer with hormone-receptor (ER/PR) positive, human epidermal growth factor receptor (HER) 2-negative, and axillary lymph node negative or positive (1-3 positive nodes) disease. All patients are categorized based on their scores ranging from 0-100 as follows: low (RS≤10), intermediate (RS11-25) and high risk (RS≥26). Further studies proved that adjuvant CT is beneficial in pre-menopausal women with RS 0-25, however offered no benefit to post-menopausal women in the same category. The aim of our study was to assess the implementation of these guidelines in a community hospital in an underserved area. Methods: At Mercy Catholic Medical Center, we performed a retrospective analysis on 303 female patients with newly diagnosed breast cancer, identified between January 2017 – October 2022. We included patients with ER/PR+, HER2-, lymph node negative or positive, who had undergone surgery and were to receive endocrine therapy with or without adjuvant CT. Patients who were lost to follow-up or did not undergo the genetic testing were excluded from the study. We then analyzed the treatment strategies based on RS categories. All patients who did not receive CT was either because it was not indicated (old age, post-menopausal) or patients refused. Results: 81 patients underwent ODX testing among whom, 60.5%, 35.8%, and 3.7% patients were Black, White and Hispanic/Asian, respectively. 1.2%, 9.8%, 18.51%, 34.56%, 35.08% were aged ≤40, 41-50, 51-60, 61-70 and ≥71 years, respectively. Based on the RS, we identified 29.62% in low risk, 56.79% in intermediate risk, and 13.5% in high-risk categories. 100% patients in the high-risk category were prescribed CT and only 7.4% patients with RS 0-25 received CT. 12 patients were found to be lymph node positive, among whom, 3 had RS≥26 and 2 were pre-menopausal, all of whom were prescribed CT. Out of these, 7 were post-menopausal with RS 0-25 and only 1 received CT. Conclusions: Our hospital data suggests that implementation of ODX and adherence to its guidelines has significantly helped avoid CT and its related side effects in the low and intermediate risk categories. Implementation of this cost-effective test has consistently increased in the last two decades and is now an imperative tool in clinical decision-making specially in community hospitals serving underprivileged populations. [Table: see text]
Genomic analysis in <i>NF2</i> meningiomas: Does co-mutation suggest new subgroups?
Authors: Yanfeng Xi, Didi Guo, Tiantian Han, Rongrong Kong, Siqi Chen, Ran Ding, Wanglong Deng, Fanfeng Bu, Shangzhi Cao
Journal: Journal of Clinical Oncology (2023)

e14058 Background: Meningiomas are the most common primary central nervous system tumours in the adults, accounting for approximately 30% of intracranial tumours. NF2 alterations are the most common genetic abnormality in meningiomas and are known to initiate events for aggressive-type meningiomas. The purpose of this study was to explore genomic characteristics of co-mutated genes in NF2 meningiomas. Methods: This study retrospectively analyzed the genomic alteration of 347 Chinese Meningioma patients during 2019-2022. Next-generation sequencing (NGS) was performed to detect gene mutations in tumor samples of the patients. Results: NF2 mutations were observed in 160 of 347 patients (46%). Our results showed the NF2-mutant patients tended to have older age compared with NF2-wildtype patients (average age: 56 vs. 47, p &lt; 0.05), and meningiomas were more common in women in both groups. TERT promoter mutation or CDKN2A/B deletion occurred in 16/160 (10%) of all NF2-mutant meningiomas. The proportion of NF2 alterations in tumors that harbored CDKN2A/B deletion or TERT promoter mutation was similar to those without mutations (41.0% vs. 46.8%, χ2＝0.46, p &gt; 0.05). 11 patients defined as NF2-mutant meningiomas were found to co-occurred with POLR2A (n = 3), TRAF7 (n = 3), PIK3CA (n = 2), PIK3R1 (n = 2), AKT1 (n = 1), SMO (n = 1), which were previously reported in a mutually exclusive pattern, identifying unique clinical cohorts. Surprisingly, we observed co-mutation in [ NF2 - TRAF7- PIK3CA] genes in a 43-year-old woman meningioma patient. Conclusions: In summary, NF2-mutant patients were observed in 46% Chinese meningioma population and tended to have older age. Interestingly, POLR2A, TRAF7, PIK3CA, PIK3R1, AKT1 and SMO mutations are reported as exclusive of NF2 mutations, were observed in 11 NF2-mutant patients in this study. The co-mutation of different driver genes in meningioma should be given enough attention, and their clinical significance remain further study.
Construction of a prognostic hierarchical model for patients with HER2 positive breast cancer with brain metastases.
Authors: Jiaxin Chen, Sh Yuan, Huiqiang Zhang, Jinmei Zhou, Zefei Jiang, Tao Wang
Journal: Journal of Clinical Oncology (2023)

e13030 Background: Brain metastasis occurs in about 50% of advanced HER2-positive breast cancer patients. In clinical practice, we need accurate model to predict the patients’ survival time. According to survival time, we can arrange reasonable treatment strategy for HER2 positive breast cancer with brain metastases. Methods: The study recruited HER2-positive breast cancer brain metastasis (BCBM) patients who attended the Fifth Medical Center of PLA General Hospital from June 2003 to June 2022.All statistics were performed using SPSS version 22.0 and R version 3.4.3 software. Results: This study included 300 patients with HER2-positive BCBM. The median age at Brain Metastases diagnosis was 48.5 years, and the median Brain Metastases Overall Survival time (BMOS) was 18.0 months (95% CI: 14.6-21.4). A single-factor analysis of BMOS revealed that age, number of brain metastasis lesions, number of extracranial lesions during BCBM, radiotherapy after BCBM, anti-HER2 therapy after BCBM, and survival prognosis after BCBM were associated with survival prognosis after diagnosis of BCBM. According to a multi-factor analysis, the age, the number of brain metastases, radiotherapy after BCBM, and anti-HER2 therapy after BCBM were all independent factors influencing survival after diagnosis of BCBM. Different independent prognostic factors comprised the patient hierarchical evaluation model. Patients' warning scores range from 0 to 7. We divided the patients into three groups with obvious differences in prognosis： Low- intermediate-risk (score≥1), stroke group (score≥3) and high-risk group (score≥6). The patient prognosis was worse when the warning score was high. The results of Kaplan-Meier survival curve analysis showed significant prognosis differences between the three groups of patients (P &lt; 0.0001). The mean Area Under Curve of the receiver operating characteristic curve for 1-yeasr, 2-year, and 3-year prognosis prediction was 0.69,0.71, and 0.67, respectively. For low-risk patients, the prognosis was significantly improved by using any anti-HER2 medications (P&lt;0.05). Trastuzumab + Pertuzumab can significantly improve the prognosis of patients at intermediate risk (P&lt;0.001, HR=0.24,95%CI: 0.13-0.43). Patients in the intermediate-risk group received both anti-HER2 medication and combined radiotherapy significantly prolonged BMOS in patients who received only drug therapy or radiotherapy (P=0.0132). Conclusions: A survival and prognostic stratification model was constructed based on the clinicopathological characteristics and treatment pattern of a large cohort of HER2-positive breast cancer patients with brain metastases, and the patients were divided into the low-risk group, intermediate-risk group and high-risk group. The optimal individualized treatment strategy was recommended according to different groups.